Meteorological satellites operating in geostationary orbits around the Earth provide observations of the Earth's surface and clouds. Images in or near the visible spectral domain can be used for the weather forecast and for monitoring important climate variables such as the surface insolation, surface albedo, pollution, smog and cloud characteristics. In some examples, such meteorological satellites can employ hyperspectral imaging.
Hyperspectral imaging, like other spectral imaging, collects and processes information across the electromagnetic spectrum. The aim of hyperspectral imaging is to obtain the spectrum for each pixel in the image of a scene, with the purpose of finding objects, identifying materials, or detecting processes.
Calibrating imagers is a common pre-processing step for remote sensing analysts that need to extract data and create scientific products from images. Calibration attempts to compensate for radiometric errors from sensor defects, variations in scan angle, and system noise to produce an image that represents true spectral radiance at the sensor.